title: WEP: a high-performance analysis pipeline for whole-exome data.
abstract: BACKGROUND
  The advent of massively parallel sequencing technologies (Next Generation Sequencing, NGS) profoundly modified the landscape of human genetics.In particular, Whole Exome Sequencing (WES) is the NGS branch that focuses on the exonic regions of the eukaryotic genomes; exomes are ideal to help us understanding high-penetrance allelic variation and its relationship to phenotype. A complete WES analysis involves several steps which need to be suitably designed and arranged into an efficient pipeline.Managing a NGS analysis pipeline and its huge amount of produced data requires non trivial IT skills and computational power.
  
  
  RESULTS
  Our web resource WEP (Whole-Exome sequencing Pipeline web tool) performs a complete WES pipeline and provides easy access through interface to intermediate and final results. The WEP pipeline is composed of several steps:1) verification of input integrity and quality checks, read trimming and filtering; 2) gapped alignment; 3) BAM conversion, sorting and indexing; 4) duplicates removal; 5) alignment optimization around insertion/deletion (indel) positions; 6) recalibration of quality scores; 7) single nucleotide and deletion/insertion polymorphism (SNP and DIP) variant calling; 8) variant annotation; 9) result storage into custom databases to allow cross-linking and intersections, statistics and much more. In order to overcome the challenge of managing large amount of data and maximize the biological information extracted from them, our tool restricts the number of final results filtering data by customizable thresholds, facilitating the identification of functionally significant variants. Default threshold values are also provided at the analysis computation completion, tuned with the most common literature work published in recent years.
  
  
  CONCLUSIONS
  Through our tool a user can perform the whole analysis without knowing the underlying hardware and software architecture, dealing with both paired and single end data. The interface provides an easy and intuitive access for data submission and a user-friendly web interface for annotated variant visualization.Non-IT mastered users can access through WEP to the most updated and tested WES algorithms, tuned to maximize the quality of called variants while minimizing artifacts and false positives.The web tool is available at the following web address: http://www.caspur.it/wep.
authors.affiliation: Dipartimento di Bioscienze, Biotecnologie e Scienze Farmacologiche, Università degli Studi di Bari, Bari, Italy.
authors.forename: Mattia
authors.initials: M
authors.lastname: D'Antonio
authors.forename: Paolo
authors.initials: P
authors.lastname: D'Onorio De Meo
authors.forename: Daniele
authors.initials: D
authors.lastname: Paoletti
authors.forename: Berardino
authors.initials: B
authors.lastname: Elmi
authors.forename: Matteo
authors.initials: M
authors.lastname: Pallocca
authors.forename: Nico
authors.initials: N
authors.lastname: Sanna
authors.forename: Ernesto
authors.initials: E
authors.lastname: Picardi
authors.forename: Graziano
authors.initials: G
authors.lastname: Pesole
authors.forename: Tiziana
authors.initials: T
authors.lastname: Castrignanò
mesh_terms: D000465:Algorithms; D059472:Exome; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D054643:INDEL Mutation; D020407:Internet; D020641:Polymorphism, Single Nucleotide; D012984:Software; D014584:User-Computer Interface